Comparative Analysis of Classifiers for the Assessment of Respiratory Disorders Using Speech Parameters by Poonam Shrivastava, Neeta Tripathi, Bikesh Kumar Singh, Bhupesh Kumar Dewangan

“…In the assessment of respiratory disorders, machine learning may play a very essential role. Respiratory disorders lead to variation in the production of speech as both go hand in hand. …”
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Contribution of groundwater quality to the industrialization of textile sector in Bangladesh by Md. Mahabub Hasan, Makoto Takafuji, Md. Shahruzzaman

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Predictive maintenance of belt conveyor drives based on the analysis of lubricating oil parameters by Kuzin E.G., Mamaeva M.S., Komarov D.S.

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Smart solutions for dissolved oxygen control in semi-batch fermenters: A machine learning approach by J. Sumathi, P. Aravind, G. Gandhimathi

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Scanning Electron Microcopy Analysis after Electrical Discharge Machining of Advanced Ni-Based Alloy by Anand Pandey, Ashish Goyal, Ranjan Walia, Varun Jurwall

Subjects: “…electrical discharge machining (EDM)…”
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A New Approach to Designing Advance Stress Release Boreholes to Mitigate Rockburst Hazards in Deep Boring-Machine-Constructed Tunnels by Zhenkun Xie, Shili Qiu, Shaojun Li, Yaxun Xiao, Minzong Zheng, Zhihao Kuang

“…This study proposes a parameter design method for ASRBs in the potential rockburst seismic source area of deeply buried hard rock TBM tunnels, including test scheme establishment methods, parameter selection methods, and parameter space relationship and evaluation index establishment methods. …”
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Impact of Gait Parameters and Their Variability on Fall Risk Assessment Accuracy Using Wearable Sensor by Jinghao Cai, Zeyang Guan, Jiachen Wang, Ziyun Ding, Yibin Li, Rui Song, Huanghe Zhang

“…This study introduced three fundamental machine learning models—logistic regression, support vector machines (SVM), and an artificial neural network—to predict fall risk among 163 frail older adults. …”
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Diagnosing schizophrenia with routine blood tests: a comparative analysis of machine learning algorithms by Yavuz Selim Ogur, Ayse Erdogan Kaya, Nur Banu Ogur, Beyza Erdogan Akturk

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Introducing the DREAMS Project: DaRk mattEr and Astrophysics with Machine Learning and Simulations by Jonah C. Rose, Paul Torrey, Francisco Villaescusa-Navarro, Mariangela Lisanti, Tri Nguyen, Sandip Roy, Kassidy E. Kollmann, Mark Vogelsberger, Francis-Yan Cyr-Racine, Mikhail V. Medvedev, Shy Genel, Daniel Anglés-Alcázar, Nitya Kallivayalil, Bonny Y. Wang, Belén Costanza, Stephanie O’Neil, Cian Roche, Soumyodipta Karmakar, Alex M. Garcia, Ryan Low, Shurui Lin, Olivia Mostow, Akaxia Cruz, Andrea Caputo, Arya Farahi, Julian B. Muñoz, Lina Necib, Romain Teyssier, Julianne J. Dalcanton, David Spergel

“…We introduce the DaRk mattEr and Astrophysics with Machine learning and Simulations (DREAMS) project, an innovative approach to understanding the astrophysical implications of alternative dark matter (DM) models and their effects on galaxy formation and evolution. …”
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Basic principles of the continuous casting technology development for machine‑building blanks by E. B. Demchenko, E. I. Marukovich

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A comprehensive investigation of morphological features responsible for cerebral aneurysm rupture using machine learning by Mostafa Zakeri, Amirhossein Atef, Mohammad Aziznia, Azadeh Jafari

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Breakage Monitoring of Executive Body Cutters in Continuous Miner According to Mechanical Vibration Parameters. Part 2. Methodology for Creating a System for Mobile Monitoring of C... by V. K. Sheleg, A. S. Romanovich, I. A. Konopliani

“…The development of research in the field of creating a mobile monitoring system for diagnosing the technical condition of mining equipment in terms of mechanical vibration parameters is one of the most science-intensive areas. …”
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Impact of Blade Geometric Parameters on the Specific Cutting Energy of Willow (<i>Salix viminalis</i>) Stems by Tomasz Nowakowski, Karol Tucki

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Optimizing economics of machining for LM25Al/VC composite material using analytical modeling, deep neural network and GRA coupled with RSM by Mesay Alemu Tolcha, Hirpa Gelgele Lemu, Yosef Wakjira Adugna

“…Abstract This study investigates the machinability of a novel LM25 aluminum alloy reinforced with vanadium carbide composite material (LM25Al/VC) using computer numerical control (CNC) lathe operation. …”
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Parameter sensitivity analysis for diesel spray penetration prediction based on GA-BP neural network by Yifei Zhang, Gengxin Zhang, Dawei Wu, Qian Wang, Ebrahim Nadimi, Penghua Shi, Hongming Xu

“…In terms of the sensitivity to inputs, it is interesting to find that the cognition of machines is different from that of humans. When an input parameter does not have any functional relationship with other input parameters, the absence of this input parameter will lead to a significant decrease in the accuracy of the output result. …”
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High-performance machine-learning-based calibration of low-cost nitrogen dioxide sensor using environmental parameter differentials and global data scaling by Slawomir Koziel, Anna Pietrenko-Dabrowska, Marek Wojcikowski, Bogdan Pankiewicz

“…These inputs encompass differentials of environmental parameters (such as temperature, humidity, atmospheric pressure), as well as readings from both primary and supplementary low-cost NO2 detectors. …”
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Exploring the process—structure–property relationship of nylon aramid 3D printed composites and parameter optimization using supervised machine learning techniques by Mohammed Raffic Noor Mohamed, Ganesh Babu Karuppiah, Dharani Kumar Selvan, Rajasekaran Saminathan, Shubham Sharma, Shashi Prakash Dwivedi, Sandeep Kumar, Mohamed Abbas, Dražan Kozak, Jasmina Lozanovic

“…The main goals of this research are to identify the significant input parameters using supervised machine learning methods and investigate the relationship between the process, structure, and properties of components created using fused deposition modeling utilizing nylon aramid composite filaments. …”
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Clinical Laboratory Parameter–Driven Machine Learning for Participant Selection in Bioequivalence Studies Among Patients With Gastric Cancer: Framework Development and Validation Study by Byungeun Shon, Sook Jin Seong, Eun Jung Choi, Mi-Ri Gwon, Hae Won Lee, Jaechan Park, Ho-Young Chung, Sungmoon Jeong, Young-Ran Yoon

“…ObjectiveWe formulated a machine learning (ML)–based framework using clinical laboratory parameters to identify participants eligible for enrollment in a bioequivalence study. …”
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Research on Speech and Emotional Recognition Algorithm Based on Support Vector Machine by LIU Ming-zhu, LI Xiao-qin, CHEN Hong-heng

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Suspension Parameter Estimation Method for Heavy-Duty Freight Trains Based on Deep Learning by Changfan Zhang, Yuxuan Wang, Jing He

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